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On the effects of node duplication and connection-oriented constructivism in neural XCSF
2008
Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation - GECCO '08
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This paper presents the use of constructivism-inspired mechanisms within a neural learning classifier system which exploits parameter self-adaptation as an approach to realize such behavior. ...
Various network growth/regression mechanisms are implemented and their performances compared. The system uses a rule structure in which each is represented by an artificial neural network. ...
In particular, we explore the success of extensions to the XCSF-based neural LCS, N-XCSF [11] , including node duplication, and a connection-oriented neural constructivism scheme, on a real-valued version ...
doi:10.1145/1388969.1389010
dblp:conf/gecco/HowardB08
fatcat:2uhdczusnbcjridambe7fcmgqi
Knowledge Representation in Learning Classifier Systems: A Review
[article]
2015
arXiv
pre-print
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
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The current work is an attempt to find a comprehensive and yet elaborate view into the existing knowledge representation techniques in LCS domain in general and XCS in specific. ...
Recently, knowledge representation component has received great deal of attention within data mining communities due to its impacts on rule based systems in terms of efficiency and efficacy. ...
The first connection of each input node is assigned to the corresponding locus of such input and other connections are set at random. ...
arXiv:1506.04002v1
fatcat:mpwk7ga3azbh5akoe3coaydp2q